Abstract

We demonstrate that the GICS sector and industry group categorizations can be systematically reconstructed from quarterly firm fundamental data using gradient boosted tree classification with high accuracy. Model complexity and performance tradeoffs are examined and relative feature importance is described. Potential extensions are outlined including validating internal consistency of existing classification methods and reducing model complexity.

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